From GPS and Google Maps to Spatial Computing

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Course Date: 23 September 2014 to 18 November 2014 (8 weeks)

Price: free

Course Summary

This course introduces concepts, algorithms, programming, theory and design of spatial computing technologies such as global positioning systems (GPS), Google Maps, location-based services and geographic information systems. Learn how to collect, analyze, and visualize your own spatial datasets while avoiding common pitfalls and building better location-aware technologies.


Estimated Workload: 4-10 hours/week

Course Instructors

Brent Hecht

Brent Hecht is an assistant professor of computer science and engineering at the University of Minnesota. With interests that lie at the intersection of human–computer interaction, geography, and big data, his research centers on the relationship between big data and human factors such as culture. A major focus of his work involves volunteered geographic information and its application in location-aware technologies.

Dr. Hecht received a Ph.D. in computer science from Northwestern University, a Master’s degree in geography from UC Santa Barbara, and dual Bachelor’s degrees in computer science and geography from Macalester College. He was a keynote speaker at WikiSym – the premiere conference on wikis and open collaboration – and has received awards for his research at top-tier publication venues in human-computer interaction and geography (e.g. ACM CHI, COSIT). He has collaborated with Google Research, Xerox PARC, and Microsoft Research, and his work been featured in the MIT Technology Review, New Scientist, AllThingsDigital, and various international TV, radio, and Internet outlets.

Shashi Shekhar

Shashi Shekhar is a Mcknight Distinguished University Professor at the University of Minnesota (Computer Science faculty). For contributions to geographic information systems (GIS), spatial databases, and spatial data mining, he received the IEEE-CS Technical Achievement Award and was elected an IEEE Fellow as well as an AAAS Fellow. He was also named a key difference-maker for the field of GIS by the most popular GIS textbook . He has a distinguished academic record that includes 280+ refereed papers, a popular textbook on Spatial Databases (Prentice Hall, 2003) and an authoritative Encyclopedia of GIS (Springer, 2008).

Course Description

From Google Maps to consumer global positioning system (GPS) devices, spatial technology shapes many lives in both ordinary and extraordinary ways. Thanks to spatial computing, a hiker in Yellowstone and a taxi driver in Manhattan can know precisely where they are, discover nearby points of interest and learn how to reach their destinations. Spatial computing technology is what powers the Foursquare check-in, the maps app on your smartphone, the devices used by scientists to track endangered species, the routing directions that help you get from point A to point B, the precision agriculture technology that is revolutionizing farming, and the augmented reality devices like Google Glass that may soon mediate our interaction with the real world.

This course introduces the fundamental ideas underlying spatial computing services, systems, and sciences. Topics covered will include the nature of geospatial information, proper statistical frameworks for working with geospatial data, key algorithms and data structures, spatial data mining, and cartography/geovisualization. We will also address applied topics such as where to find spatial data, how to use powerful open source software to analyze and map spatial data, and frameworks for building location-based services.


Three Ways to Enjoy this Course:

This course is designed to support three different types of students and educational goals:

Curiosity Track: Most of us interact with spatial technologies every day. This track is for students who wish to learn about one or two spatial computing topics, but not commit to an entire course. Curiosity track students are not interested in a certificate of accomplishment.

Concepts Track: This track is for students who want to learn about spatial computing concepts in order to make informed choices, but who are not programmers and do not have extensive experience with statistical methods. For example, concepts track students will learn about Tobler’s First Law of geography and map projections, but will not delve into the quantifications of either. Students who complete the concepts track with sufficiently high scores will receive a Statement of Accomplishment.

Technical Track: This track builds on the concepts track, but adds math and programming. For example, we will cover spatial statistical indicators like Moran’s I and Ripley’s K when discussing Tobler’s First Law and will have students calculate the distance between two points using two different coordinate systems and open-source APIs. Students who complete the technical track with sufficiently high scores will receive a Distinguished Statement of Accomplishment.

Syllabus

Topics Covered:
Module 1 - Introduction
Course Introduction
Defining Spatial Computing
Course Structure
Interviews with Johannes Schöning, Loren Terveen and Martin Raubal
Module 2 - Spatial Query Languages
What is a Query? Query Language?
An example database with 3 tables
SQL overview
SELECT statement with 1 table
Multi-table SELECT statement
Why spatial extensions are needed
1-table spatial queries
Trends
Module 3 - Spatial Networks
Motivation, Societal use cases
Example spatial networks
Conceptual and mathematical models
Need for SQL extensions
CONNECT statement
RECURSIVE statement
Storage and data structures
Algorithms for connectivity query
Algorithms for shortest path
Interviews with Dev Oliver and Betsy George
Module 4 - Spatial Data Mining
Motivation, Spatial Pattern Families
Spatial data types and relationships
Limitations of Traditional Statistics
Location Prediction model
Hotspots
Spatial outliers
Colocations and Co-occurrences
Summary: What is special about mining spatial data?
Module 5 - Volunteered Geographic Information (VGI)
Introduction to Volunteered Geographic Information
Producing VGI
Pros and Cons of VGI
Interview with Michael Goodchild
Module 6 - Positioning
Introduction to Positioning
Overview of GPS
Overview of Wifi and Cellular Positioning
Introduction to Content-based Positioning
Geoparsing
Location-field Positioning
Module 7 - Cartography
Introduction to Cartography
Overview of Maps and Mapping
Reference Maps
Thematic Maps
Spatialization
Module 8 - Future Directions
Introduction
Spatial Databases: Representative projects
Data Mining: Representative projects
Advances in Cartography
Advances in Positioning
Interviews with Vipin Kumar, Wan Bae, Mohammed Mokbel and Len Kne

Format

Students in this course will learn through topical lectures as well as interviews with and guest lectures from academic and industry experts.

Course Workload

4-10 hours/week

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